Developing trust and confidence in the delivery of Ai-Oriented teaching strategies among Non-ICT expert teachers

Information Communication and Technology (ICT) introduces intelligent, adaptive, and data-driven tools that enhance both teaching and learning processes, helping transform the education system today. Artificial Intelligence (AI) streamlines administrative and instructional tasks for educators, such as grading, content generation, and curriculum planning, freeing up time for more meaningful student-teacher interaction. However, concerns persist regarding the ethical implications, data privacy risks, and over-reliance on AI systems in the classroom. This paper explored different factors that could influence teachers’ confidence and trust in the use of AI in classrooms. Eighteen instructors from Iloilo, Zamboanga City, and Surigao City were purposively sampled and interviewed, and the data were analyzed thematically following Braun and Clarke’s[1] approach. The study revealed that non-ICT expert teachers generally perceived AI integration as disruptive to their instructional flow, with 72% reporting misalignment with established teaching strategies, 61% noting increased student passivity, and over half citing frequent technical complications that hindered classroom productivity. Teachers expressed that AI tools often lacked contextual sensitivity and failed to support spontaneous teacher-student interaction, with some viewing these tools as undermining their pedagogical autonomy. The development of trust and confidence in AI technologies among these teachers was found to be heavily influenced by three major factors: structured training, improved curriculum guidelines, and institutional support. Interpreted through the Technology Acceptance Model (TAM), these findings highlight how perceived ease of use, perceived usefulness, and attitudes toward AI shaped teachers’ behavioral intention. Consequently, effective AI adoption among non-ICT expert teachers required more than technical functionality. It demanded systemic, pedagogical, and psychological alignment to ensure sustainable, confident, and meaningful use of AI in education. Future research should design and test AI-focused teacher training programs, investigate curriculum-level integration policies (e.g., through the Philippine Department of Education), and explore AI tool designs that preserve teacher autonomy while supporting student engagement.